ESD.10 Introduction to Technology and Policy (MIT)
This course explores perspectives in the policy process - agenda setting, problem definition, framing the terms of debate, formulation and analysis of options, implementation and evaluation of policy outcomes using frameworks including economics and markets, law, and business and management. Methods include cost/benefit analysis, probabilistic risk assessment, and system dynamics. Exercises include developing skills to work on the interface between technology and societal issues; simulation exer
1.101 Introduction to Civil and Environmental Engineering Design I (MIT)
In this sophomore design course, you will be challenged with three design tasks: a first concerning water resources/treatment, a second concerning structural design, and a third focusing on the conceptual (re)design of a large system, Boston's Back Bay. The first two tasks require the design, fabrication and testing of hardware. Several laboratory experiments will be carried out and lectures will be presented to introduce students to the conceptual and experimental basis for design in both domai
2.001 Mechanics & Materials I (MIT)
This course provides an introduction to the mechanics of solids with applications to science and engineering. We emphasize the three essential features of all mechanics analyses, namely: (a) the geometry of the motion and/or deformation of the structure, and conditions of geometric fit, (b) the forces on and within structures and assemblages; and (c) the physical aspects of the structural system (including material properties) which quantify relations between the forces and motions/deformation.
6.034 Artificial Intelligence (MIT)
6.034 is the header course for the department's "Artificial Intelligence and Applications" concentration. This course introduces students to the basic knowledge representation, problem solving, and learning methods of artificial intelligence. Upon completion of 6.034, students should be able to: develop intelligent systems by assembling solutions to concrete computational problems, understand the role of knowledge representation, problem solving, and learning in intelligent-system engineering, a
2.141 Modeling and Simulation of Dynamic Systems (MIT)
This course models multi-domain engineering systems at a level of detail suitable for design and control system implementation. Topics include network representation, state-space models; multi-port energy storage and dissipation, Legendre transforms; nonlinear mechanics, transformation theory, Lagrangian and Hamiltonian forms; and control-relevant properties. Application examples may include electro-mechanical transducers, mechanisms, electronics, fluid and thermal systems, compressible flow, ch
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